Abstract
The study on the "Technology Innovations in Supply Chains: Unlocking Sustainability and SDG Advancement," offers a thorough examination of the intricate connections between technological innovation, supply chain management, sustainability development, and the advancement of the Sustainable Development Goals (SDGs) in various Chinese cities. The study explores how developments in artificial intelligence (A.I.), the Internet of Things (IoT), and big data have changed supply chain practices and their consequent effects on environmental and sustainability results. It does this by utilizing a substantial dataset spanning a decade. The findings showed that different patterns of technological adoption and their impacts might be seen in the assessed cities. While it is clear that technology innovation is essential for improving supply chain effectiveness and encouraging sustainability, not all regions see the same advantages. Variations in supply chain complexity, city size, technology advancement, and environmental legislation are all blamed for these discrepancies. The report also offers detailed knowledge of the connection between the development of modern supply chains and the advancement of the SDGs. Even though many cities showed high relationships, others showed less alignment, pointing to the importance of additional economic, sociopolitical, and environmental factors. The report concludes by highlighting the potential of technology to advance sustainability and the SDGs while emphasizing the necessity for a deliberate and context-specific approach to technology integration. Additionally, it emphasizes how crucial supportive regulations are in maximizing the advantages. These findings significantly impact business executives, educators, and legislators who want to use technology to advance sustainability and the SDGs.
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Akhtar N, Siddiqi UI, Akhtar MN, Usman M, Ahmad W (2020) Modeling attitude ambivalence and behavioral outcomes from hotel reviews. Int J Contemp Hosp Manag 32(9):2831–2855. https://doi.org/10.1108/IJCHM-11-2019-0962
Apergis N (2019) Chapter 6 - Renewable Energy and its Finance as a Solution to the Environmental Degradation. In: Özcan B, Öztürk E (Eds.), Environmental Kuznets Curve (EKC). Academic Press, pp. 55–63. https://doi.org/10.1016/B978-0-12-816797-7.00006-0
Benmelech E, Tzur-Ilan N (2020) The Determinants of Fiscal and Monetary Policies During the COVID-19 Crisis. In SSRN Electronic Journal. National Bureau of Economic Research. https://doi.org/10.2139/ssrn.3634549
Bera K, Schalper KA, Rimm DL, Velcheti V, Madabhushi A (2019) Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology. Nat Rev Clin Oncol 16(11):703–715. https://doi.org/10.1038/S41571-019-0252-Y
Biermann P (2016) How fuel poverty affects subjective well-being: panel evidence from Germany. Oldenburg Discussion Papers in Economics
Charlier D, Kahouli S (2019) From residential energy demand to fuel poverty: income-induced non-linearities in the reactions of households to energy price fluctuations. Energy J 40(2):101–137
Chien F, Ajaz T, Andlib Z, Chau KY, Ahmad P, Sharif A (2021) The role of technology innovation, renewable energy and globalization in reducing environmental degradation in Pakistan: A step towards sustainable environment. Renew Energy 177:308–317. https://doi.org/10.1016/J.RENENE.2021.05.101
Chien FS, Hsu CC, Andlib Z, Shah MI, Ajaz T, Genie MG (2022) The role of solar energy and eco-innovation in reducing environmental degradation in China: Evidence from QARDL approach. Integr Environ Assess Manag 18(2):555–571. https://doi.org/10.1002/IEAM.4500
Creutzfeldt N, Gill C, McPherson R, Cornelis M (2020) The Social and Local Dimensions of Governance of Energy Poverty: Adaptive Responses to State Remoteness. J Consum Policy. https://doi.org/10.1007/s10603-019-09442-z
Dunning JH (1988) The Eclectic Paradigm of International Production: A Restatement and Some Possible Extensions. J Int Bus Stud 19(1):1–31. https://doi.org/10.1057/PALGRAVE.JIBS.8490372
El Akremi A, Gond JP, Swaen V, De Roeck K, Igalens J (2018) How Do Employees Perceive Corporate Responsibility? Development and Validation of a Multidimensional Corporate Stakeholder Responsibility Scale. J Manag. https://doi.org/10.1177/0149206315569311
Farfan J, Breyer C (2017) Structural changes of global power generation capacity towards sustainability and the risk of stranded investments supported by a sustainability indicator. J Clean Prod 141:370–384. https://doi.org/10.1016/j.jclepro.2016.09.068
Hafeez M, Yuan C, Shahzad K, Aziz B, Iqbal K, Raza S (2019) An empirical evaluation of financial development-carbon footprint nexus in One Belt and Road region. Environ Sci Pollut Res 26(24):25026–25036. https://doi.org/10.1007/S11356-019-05757-Z
Hu F, Xi X, Zhang Y (2021) Influencing mechanism of reverse knowledge spillover on investment enterprises’ technological progress: An empirical examination of Chinese firms. Technol Forecast Soc Chang 169:120797. https://doi.org/10.1016/J.TECHFORE.2021.120797
Huang TH, Liu NH, Kumbhakar SC (2018) Joint estimation of the Lerner index and cost efficiency using copula methods. Empir Econ 54(2):799–822. https://doi.org/10.1007/s00181-016-1216-z
Işık C, Sirakaya-Turk E, Ongan S (2019) Testing the efficacy of the economic policy uncertainty index on tourism demand in USMCA: Theory and evidence. Tour Econ 26(8):1344–1357. https://doi.org/10.1177/1354816619888346
Iyer G, Calvin K, Clarke L, Edmonds J, Hultman N, Hartin C, McJeon H, Aldy J, Pizer W (2018) Implications of sustainable development considerations for comparability across nationally determined contributions. Nat Clim Chang. https://doi.org/10.1038/s41558-017-0039-z
Khan AQ, Saleem N, Fatima ST (2018) Financial development, income inequality, and CO2 emissions in Asian countries using STIRPAT model. Environ Sci Pollut Res 25(7):6308–6319. https://doi.org/10.1007/s11356-017-0719-2
Li QK, Lin H, Tan X, Du S (2020) H∞Consensus for Multiagent-Based Supply Chain Systems under Switching Topology and Uncertain Demands. IEEE Trans Syst, Man, Cybern: Syst 50(12):4905–4918. https://doi.org/10.1109/TSMC.2018.2884510
Li X, Ozturk I, Ullah S, Andlib Z, Hafeez M (2022) Can top-pollutant economies shift some burden through insurance sector development for sustainable development? Econ Anal Policy 74:326–336. https://doi.org/10.1016/j.eap.2022.02.006
Li J, Yang X, Shi V, Cai G (2023) Partial centralization in a durable-good supply chain. Prod Oper Manag. https://doi.org/10.1111/POMS.14006
Liu X, Shi T, Zhou G, Liu M, Yin Z, Yin L, Zheng W (2023a) Emotion classification for short texts: an improved multi-label method. Humanit Soc Sci Commun 10(1):1–9. https://doi.org/10.1057/s41599-023-01816-6
Liu X, Zhou G, Kong M, Yin Z, Li X, Yin L, Zheng W (2023b) Developing Multi-Labelled Corpus of Twitter Short Texts: A Semi-Automatic Method. Systems 11(8):390. https://doi.org/10.3390/SYSTEMS11080390
Livieris IE, Pintelas E, Pintelas P (2020) A CNN–LSTM model for gold price time-series forecasting. Neural Comput Appl 32(23):17351–17360. https://doi.org/10.1007/S00521-020-04867-X
Lu S, Liu M, Yin L, Yin Z, Liu X, Zheng W (2023) The multi-modal fusion in visual question answering: a review of attention mechanisms. PeerJ Comput Sci 9:e1400. https://doi.org/10.7717/PEERJ-CS.1400
Lyytimäki J, Nygrén NA, Pulkka A, Rantala S (2018) Energy transition looming behind the headlines? Newspaper coverage of biogas production in Finland. Energy Sustain Soc 8(1). https://doi.org/10.1186/S13705-018-0158-Z
Mahmood N, Wang Z, Hassan ST (2019) Renewable energy, economic growth, human capital, and CO2 emission: an empirical analysis. Environ Sci Pollut Res 26(20):20619–20630. https://doi.org/10.1007/S11356-019-05387-5
Malliet P, Reynès F, Landa G, Hamdi-Cherif M, Saussay A (2020) Assessing Short-Term and Long-Term Economic and Environmental Effects of the COVID-19 Crisis in France. Environ Resour Econ 76(4):867–883. https://doi.org/10.1007/s10640-020-00488-z
Marler JH, Parry E (2016) Human resource management, strategic involvement and e-HRM technology. Int J Hum Resour Manag 27(19):2233–2253
Meyer S, Laurence H, Bart D, Middlemiss L, Maréchal K (2018) Capturing the multifaceted nature of energy poverty: Lessons from Belgium. Energy Res Soc Sci 40:273–283. https://doi.org/10.1016/j.erss.2018.01.017
Mirza N, Afzal A, Umar M, Skare M (2023) The impact of green lending on banking performance: Evidence from SME credit portfolios in the BRIC. Econ Anal Policy 77:843–850. https://doi.org/10.1016/J.EAP.2022.12.024
Pencarelli T (2020) The digital revolution in the travel and tourism industry. Inform Technol Tour 22(3):455–476
Porter ME, Van Der Linde C (2017) Toward a new conception of the environment-competitiveness relationship. Corp Environ Responsib 9(4):61–82. https://doi.org/10.1257/jep.9.4.97
Qiu L, Yu R, Hu F, Zhou H, Hu H (2023) How can China’s medical manufacturing listed firms improve their technological innovation efficiency? An analysis based on a three-stage DEA model and corporate governance configurations. Technol Forecast Soc Chang 194:122684. https://doi.org/10.1016/J.TECHFORE.2023.122684
Raikar S, Adamson S (2020) 13 - Renewable energy finance in the international context. In: Raikar S, Adamson S (Eds.), Renewable Energy Finance. Academic Press, pp. 185–220. https://doi.org/10.1016/B978-0-12-816441-9.00013-1
Ren X, Shao Q, Zhong R (2020) Nexus between green finance, non-fossil energy use, and carbon intensity: Empirical evidence from China based on a vector error correction model. J Clean Prod 277:122844. https://doi.org/10.1016/j.jclepro.2020.122844
Sciomer S, Moscucci F, Magrì D, Badagliacca R, Piccirillo G, Agostoni P (2020) SARS-CoV-2 spread in Northern Italy: what about the pollution role? Environ Monit Assess 192(6). https://doi.org/10.1007/s10661-020-08317-y
Sueyoshi T, Goto M (2012) Data envelopment analysis for environmental assessment: comparison between public and private ownership in petroleum industry. Eur J Oper Res 216(3):668–678
Sun Y, Yesilada F, Andlib Z, Ajaz T (2021) The role of eco-innovation and globalization towards carbon neutrality in the USA. J Environ Manag 299:113568. https://doi.org/10.1016/J.JENVMAN.2021.113568
Sun Y, Li H, Andlib Z, Genie MG (2022) How do renewable energy and urbanization cause carbon emissions? Evidence from advanced panel estimation techniques. Renew Energy 185:996–1005. https://doi.org/10.1016/J.RENENE.2021.12.112
Trotta G (2020) Assessing drivers of energy consumption and progress toward energy targets in Italy. Energy Sources Part B 15(3):137–156
Udemba EN, Magazzino C, Bekun FV (2020) Modeling the nexus between pollutant emission, energy consumption, foreign direct investment, and economic growth: new insights from China. Environ Sci Pollut Res 27(15):17831–17842. https://doi.org/10.1007/s11356-020-08180-x
Usmani RA (2020) Potential for energy and biofuel from biomass in India. Renew Energy 155:921–930. https://doi.org/10.1016/j.renene.2020.03.146
Wu B, Gu Q, Liu Z, Liu J (2023) Clustered institutional investors, shared ESG preferences and low-carbon innovation in family firm. Technol Forecast Soc Chang 194:122676. https://doi.org/10.1016/J.TECHFORE.2023.122676
Xu X, Wang C, Zhou P (2021) GVRP considered oil-gas recovery in refined oil distribution: From an environmental perspective. Int J Prod Econ 235:108078. https://doi.org/10.1016/J.IJPE.2021.108078
Xu J, Yang Z, Wang Z, Li J, Zhang X (2023) Flexible sensing enabled packaging performance optimization system (FS-PPOS) for lamb loss reduction control in E-commerce supply chain. Food Control 145:109394. https://doi.org/10.1016/J.FOODCONT.2022.109394
Xue Y, Ye X, Zhang W, Zhang J, Liu Y, Wu C, Li Q (2020) Reverification of the “resource curse” hypothesis based on industrial agglomeration: Evidence from China. J Clean Prod 275. https://doi.org/10.1016/J.JCLEPRO.2020.124075
Yan L, Yin-He S, Qian Y, Zhi-Yu S, Chun-Zi W, Zi-Yun L (2021) Method of Reaching Consensus on Probability of Food Safety Based on the Integration of Finite Credible Data on Block Chain. IEEE Access 9:123764–123776. https://doi.org/10.1109/ACCESS.2021.3108178
Yoshino N, Taghizadeh-Hesary F, Otsuka M (2020) Covid-19 and Optimal Portfolio Selection for Investment in Sustainable Development Goals. Financ Res Lett. https://doi.org/10.1016/j.frl.2020.101695
Young KG (2020) The idea of a human rights-based economic recovery after COVID-19. Int J Public Law Policy 6(4):1. https://doi.org/10.1504/ijplap.2020.10037231
Zhao C, Zhong S, Zhang X, Zhong Q, Shi K (2020) Novel results on nonfragile sampled-data exponential synchronization for delayed complex dynamical networks. Int J Robust Nonlinear Control 30(10):4022–4042. https://doi.org/10.1002/rnc.4975
Zhong S, Pantelous AA, Goh M, Zhou J (2019) A reliability-and-cost-based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms. Mech Syst Signal Process 124:643–663. https://doi.org/10.1016/j.ymssp.2019.02.012
Zhou Z, Yang C, Ye J (2018) Perforation of Palate in Granulomatosis With Polyangiitis. JCR: J Clin Rheumato 1. https://doi.org/10.1097/00124743-900000000-99214
Zhu J, Shi H, Song B, Tan S, Tao Y (2020) Deep neural network based recursive feature learning for nonlinear dynamic process monitoring. Can J Chem Eng 98(4):919–933. https://doi.org/10.1002/cjce.23669
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This work was supported by the Henan Office of Philosophy and Social Science Foundation (2021CJJ139). This work was supported by the soft science project of Henan Province (232400410056). This work was supported by the doctoral research project of Henan Institute of Animal Husbandry Economics (906/M4050015).
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Haiyang Hu: Conceptualization, Data curation, Methodology, Writing—original draft, Chen Yao: Data curation, Visualization, supervision, editing, Writing—review & editing, and software.
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Hu, H., Yao, C. Technology innovations in supply chains: Unlocking Sustainability and SDG Advancement. Environ Sci Pollut Res 30, 102725–102738 (2023). https://doi.org/10.1007/s11356-023-29538-x
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DOI: https://doi.org/10.1007/s11356-023-29538-x